relf · relf · Jul 7, 2026 · May 28, 2026 · Jun 11, 2026 · Jun 12, 2026
diff --git a/.github/copilot-instructions.md b/.github/copilot-instructions.md
@@ -147,7 +147,7 @@ let model = Model::load("model.json")?;
 - [crates/gpx/README.md](../crates/gpx/README.md): Gpx command usage and format options
 - [python/src/lib.rs](../python/src/lib.rs): PyO3 module definition
 - [python/src/egor.rs](../python/src/egor.rs): Python Egor class wrapping Rust
-- [doc/](../doc/): Jupyter notebooks with tutorials
+- [notebooks/](../notebooks/): Jupyter notebooks with tutorials
 
 ## Testing Notes
 

diff --git a/.github/workflows/website.yml b/.github/workflows/website.yml
@@ -0,0 +1,115 @@
+name: website
+
+on:
+  pull_request:
+    branches: [ master ]
+    paths:
+      - .github/workflows/website.yml
+      - crates/ego/examples/**
+      - crates/gp/examples/**
+      - website/**
+      - notebooks/**
+      - python/egobox/examples/*.py
+      - python/egobox/tests/*.py
+  push:
+    branches: [ master ]
+    paths:
+      - .github/workflows/website.yml
+      - crates/ego/examples/**
+      - crates/gp/examples/**
+      - website/**
+      - notebooks/**
+      - python/egobox/examples/website_*.py
+      - python/egobox/tests/test_website_examples.py
+  workflow_dispatch:
+
+permissions:
+  contents: read
+  pages: write
+  id-token: write
+
+concurrency:
+  group: website-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    env:
+      UV_CACHE_DIR: /tmp/.uv-cache
+      RUST_BACKTRACE: 1
+      MPLBACKEND: Agg
+
+    steps:
+      - uses: actions/checkout@v6
+
+      - name: Install toolchain
+        uses: actions-rs/toolchain@v1
+        with:
+          profile: minimal
+          toolchain: stable
+          override: true
+
+      - name: Set up Python
+        uses: actions/setup-python@v6
+        with:
+          python-version: '3.12'
+
+      - name: Set up uv
+        run: curl -LsSf https://astral.sh/uv/install.sh | sh
+
+      - name: Cache folder for uv
+        uses: actions/cache@v5
+        with:
+          path: /tmp/.uv-cache
+          key: uv-${{ runner.os }}-${{ hashFiles('python/uv.lock') }}
+          restore-keys: |
+            uv-${{ runner.os }}-${{ hashFiles('python/uv.lock') }}
+            uv-${{ runner.os }}
+
+      - name: Install the project
+        working-directory: python
+        run: uv sync --all-extras --dev --python 3.12
+
+      - name: Build the wrapper
+        uses: PyO3/maturin-action@v1
+        with:
+          working-directory: python
+          command: develop
+          args: --release
+
+      - name: Verify website examples
+        working-directory: python
+        run: uv run pytest egobox/tests/test_website_examples.py
+
+      - name: Install Zola
+        uses: taiki-e/install-action@v2
+        with:
+          tool: zola
+
+      - name: Build site
+        working-directory: website
+        run: zola build
+
+      - name: Configure Pages
+        if: github.event_name == 'push' && github.ref == 'refs/heads/master'
+        uses: actions/configure-pages@v5
+
+      - name: Upload Pages artifact
+        if: github.event_name == 'push' && github.ref == 'refs/heads/master'
+        uses: actions/upload-pages-artifact@v4
+        with:
+          path: website/public
+
+  deploy:
+    if: github.event_name == 'push' && github.ref == 'refs/heads/master'
+    needs: build
+    runs-on: ubuntu-latest
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+
+    steps:
+      - name: Deploy to GitHub Pages
+        id: deployment
+        uses: actions/deploy-pages@v4
diff --git a/.gitignore b/.gitignore
@@ -41,4 +41,7 @@ history*
 
 # Output directories
 **/*_output/
-**/*_out/
+**/*_out/
+
+# Generated website
+website/public
diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -257,7 +257,7 @@ See also some breaking changes description in optimizer options in PR #253
 ## Version 0.15.0 - 02/01/2024
 
 * `gp`: Implement sparse gaussian process methods (cf. `SparseGaussianProcess`)
-* Python binding: `SparseGpMix`, see doc/tutorial
+* Python binding: `SparseGpMix`, see notebooks/tutorial
 * GP/SGP API
   * hyperparameter tuning : initial theta guess and bounds can be specified (`theta_init`, `theta_bounds`)
   * `n_start` controls the number of optimization multistart
@@ -365,7 +365,7 @@ by @relf in <https://github.com/relf/egobox/pull/105>
 * `ego`:
   * Refactor `Egor` using [`argmin 0.7.0` solver framework](http://argmin-rs.org) `EgorSolver` can be used with `argmin::Executor` and benefit from observers and checkpointing features (#67)
   * `Egor` use kriging setting by default (i.e. one cluster with constant mean and squared exponential correlation model)
-* Add [notebook on Manuau Loa CO2 example](https://github.com/relf/egobox/blob/master/doc/Gpx_MaunaLoaCO2.ipynb) to show `GpMix`/`Gpx` surrogate model usage (#62)
+* Add [notebook on Manuau Loa CO2 example](https://github.com/relf/egobox/blob/master/notebooks/Gpx_MaunaLoaCO2.ipynb) to show `GpMix`/`Gpx` surrogate model usage (#62)
 * Use xoshiro instead of isaac random generator (#63)
 * Upgrade `ndarray 0.15`, `linfa 0.6.1`, `PyO3 0.17` (#57, #64)
 

diff --git a/README.md b/README.md
@@ -1,7 +1,7 @@
 <p align="center">
   <img
     width="100"
-    src="./doc/LOGO_EGOBOX_v4_100x100.png"
+    src="./website/static/img/LOGO_EGOBOX_v4_100x100.png"
     alt="Efficient Global Optimization toolbox in Rust"
   />
 </p>
@@ -70,7 +70,7 @@ plt.show()
 
 See also [this example written in Rust](crates/gp/examples/kriging.rs)
 
-See the [tutorial notebooks](https://github.com/relf/egobox/tree/master/doc/README.md) and [examples folder](https://github.com/relf/egobox/tree/d9db0248199558f23d966796737d7ffa8f5de589/python/egobox/examples) for more information on the usage of the optimizer and mixture of Gaussian processes surrogate model.
+See the [tutorial notebooks](https://github.com/relf/egobox/tree/master/notebooks/README.md) and [examples folder](https://github.com/relf/egobox/tree/d9db0248199558f23d966796737d7ffa8f5de589/python/egobox/examples) for more information on the usage of the optimizer and mixture of Gaussian processes surrogate model.
 
 ## The Rust libraries
 

diff --git a/doc/LOGO_EGOBOX_v4_100x100.png b/doc/LOGO_EGOBOX_v4_100x100.png
diff --git a/doc/Egor_Tutorial.ipynb → notebooks/Egor_Tutorial.ipynb b/doc/Egor_Tutorial.ipynb → notebooks/Egor_Tutorial.ipynb
diff --git a/doc/Gpx_MaunaLoaCO2.ipynb → notebooks/Gpx_MaunaLoaCO2.ipynb b/doc/Gpx_MaunaLoaCO2.ipynb → notebooks/Gpx_MaunaLoaCO2.ipynb
diff --git a/doc/Gpx_Tutorial.ipynb → notebooks/Gpx_Tutorial.ipynb b/doc/Gpx_Tutorial.ipynb → notebooks/Gpx_Tutorial.ipynb
diff --git a/doc/README.md → notebooks/README.md b/doc/README.md → notebooks/README.md
@@ -1,7 +1,7 @@
 <p align="center">
   <img
     width="100"
-    src="./LOGO_EGOBOX_v4_100x100.png"
+    src="../website/static/img/LOGO_EGOBOX_v4_100x100.png"
     alt="Efficient Global Optimization toolbox in Rust"
   />
 </p>
@@ -10,23 +10,23 @@
 
 ## Surrogate-based adaptative optimization: _Egor_
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/doc/Egor_Tutorial.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/notebooks/Egor_Tutorial.ipynb)
 
 ## Mixture of Gaussian process surrogates: _Gpx_
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/doc/Gpx_Tutorial.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/notebooks/Gpx_Tutorial.ipynb)
 
 ## Mixture of Gaussian process surrogates command line tool: _gpx_
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/doc/gpx_cli.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/notebooks/gpx_cli.ipynb)
 
 ## Gaussian process surrogates: _SparseGpx_
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/doc/SparseGpx_Tutorial.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/notebooks/SparseGpx_Tutorial.ipynb)
 
 ## _Gpx_ on Mauna Loa CO2 data
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/doc/Gpx_MaunaLoaCO2.ipynb)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/relf/egobox/blob/master/notebooks/Gpx_MaunaLoaCO2.ipynb)
 
 ## Solve an analytical MDO problem with a hidden optimum
 

diff --git a/doc/SparseGpx_Tutorial.ipynb → notebooks/SparseGpx_Tutorial.ipynb b/doc/SparseGpx_Tutorial.ipynb → notebooks/SparseGpx_Tutorial.ipynb
diff --git a/doc/gpx_cli.ipynb → notebooks/gpx_cli.ipynb b/doc/gpx_cli.ipynb → notebooks/gpx_cli.ipynb
@@ -34,7 +34,7 @@
    "source": [
     "## Setup\n",
     "\n",
-    "We keep tutorial artifacts in `doc/gpx_cli_tutorial` and run GPX **directly** with shell commands (`!gpx ...`) in notebook cells."
+    "We keep tutorial artifacts in `notebooks/gpx_cli_tutorial` and run GPX **directly** with shell commands (`!gpx ...`) in notebook cells."
    ]
   },
   {
@@ -397,7 +397,7 @@
     "- `gpx predict <input.csv> --model surrogate_model.gpx --output predictions.csv --with-variance`\n",
     "- `gpx py --model surrogate_model.gpx -o gpx.py`\n",
     "\n",
-    "Artifacts are stored in `doc/gpx_cli_tutorial_out`."
+    "Artifacts are stored in `notebooks/gpx_cli_tutorial_out`."
    ]
   },
   {

diff --git a/python/README.md b/python/README.md
@@ -55,4 +55,4 @@ plt.plot(xtrain, ytrain, "o")
 plt.show()
 ```
 
-See the [tutorial notebooks](https://github.com/relf/egobox/tree/master/doc/README.md) and [examples folder](https://github.com/relf/egobox/tree/d9db0248199558f23d966796737d7ffa8f5de589/python/egobox/examples) for more information on the usage of the optimizer and mixture of Gaussian processes surrogate model.
+See the [tutorial notebooks](https://github.com/relf/egobox/tree/master/notebooks/README.md) and [examples folder](https://github.com/relf/egobox/tree/d9db0248199558f23d966796737d7ffa8f5de589/python/egobox/examples) for more information on the usage of the optimizer and mixture of Gaussian processes surrogate model.
diff --git a/python/egobox/egobox.pyi b/python/egobox/egobox.pyi
@@ -13,8 +13,8 @@ __all__ = [
     "Egor",
     "EgorOptim",
     "ExitStatus",
-    "FeasibleInfillStrategy",
     "FailsafeStrategy",
+    "FeasibleInfillStrategy",
     "GpConfig",
     "GpMix",
     "Gpx",
@@ -163,9 +163,9 @@ class Egor:
             Infill criteria to decide best next promising point.
             Can be either InfillStrategy.LOG_EI, InfillStrategy.EI, InfillStrategy.WB2, InfillStrategy.WB2S
 
-        infill_optimizer (InfillOptimizer enum):
-            Internal optimizer used to optimize infill criteria.
-            Can be either InfillOptimizer.COBYLA or InfillOptimizer.SLSQP
+        feasible_infill_strategy (FeasibleInfillStrategy enum):
+            Strategy to handle feasibility information in the infill criterion.
+            Can be either FeasibleInfillStrategy.NONE, FeasibleInfillStrategy.EFI_P, or FeasibleInfillStrategy.EFI_FE
 
         cstr_infill (bool):
             Activate constrained infill criterion where the product of probability of feasibility of constraints
@@ -175,6 +175,10 @@ class Egor:
             Constraint management either use the mean value or upper bound
             Can be either ConstraintStrategy.MeanValue or ConstraintStrategy.UpperTrustedBound.
 
+        infill_optimizer (InfillOptimizer enum):
+            Internal optimizer used to optimize infill criteria.
+            Can be either InfillOptimizer.COBYLA or InfillOptimizer.SLSQP
+
         qei_config (QEiConfig):
             Configuration for parallel (qEI) evaluation also known as batch or multipoint evaluation.
             q points are selected at each iteration of the EGO algorithm.
@@ -207,30 +211,24 @@ class Egor:
 
         seed (int >= 0 or None):
             Deprecated: use seed argument in minimize() or suggest() instead.
-            Random generator seed to allow computation reproducibility.
 
         outdir (String or None):
             Deprecated: use outdir argument in minimize() instead.
-            Directory to write optimization history and used as search path for warm start doe.
 
         warm_start (bool):
             Deprecated: use warm_start argument in minimize() instead.
-            Start by loading initial doe from <outdir> directory.
 
         hot_start (bool, int >= 0 or None):
             Deprecated: use hot_start argument in minimize() instead.
-            When True, hot_start behaves like hot_start=0 with no iteration extension.
-            When hot_start>=0 saves optimizer state at each iteration and starts from a previous checkpoint.
 
         verbose (int, Verbose enum, or None):
             Deprecated: use verbose argument in minimize() instead.
-            Logging verbosity level for the optimizer.
 
     # Returns
 
         Egor object which can be used to optimize a function using the minimize method.
     """
-    def __new__(cls, xspecs: typing.Any, gp_config: GpConfig = ..., n_cstr: builtins.int = 0, cstr_tol: typing.Optional[typing.Sequence[builtins.float]] = None, cstr_specs: typing.Optional[typing.Sequence[CstrSpec]] = None, n_start: builtins.int = 20, n_doe: builtins.int = 0, doe: typing.Optional[numpy.typing.NDArray[numpy.float64]] = None, infill_strategy: InfillStrategy = InfillStrategy.LOG_EI, cstr_infill: builtins.bool = False, cstr_strategy: ConstraintStrategy = ConstraintStrategy.MC, qei_config: QEiConfig = ..., infill_optimizer: InfillOptimizer = InfillOptimizer.COBYLA, trego: typing.Optional[typing.Any] = None, coego_n_coop: builtins.int = 0, target: builtins.float = -1.7976931348623157e+308, failsafe_strategy: FailsafeStrategy = FailsafeStrategy.REJECTION, seed: typing.Optional[builtins.int] = None, outdir: typing.Optional[builtins.str] = None, warm_start: builtins.bool = False, hot_start: typing.Optional[typing.Any] = None, verbose: typing.Optional[typing.Any] = None) -> Egor: ...
+    def __new__(cls, xspecs: typing.Any, gp_config: GpConfig = ..., n_cstr: builtins.int = 0, cstr_tol: typing.Optional[typing.Sequence[builtins.float]] = None, cstr_specs: typing.Optional[typing.Sequence[CstrSpec]] = None, n_start: builtins.int = 20, n_doe: builtins.int = 0, doe: typing.Optional[numpy.typing.NDArray[numpy.float64]] = None, infill_strategy: InfillStrategy = InfillStrategy.LOG_EI, feasible_infill_strategy: FeasibleInfillStrategy = FeasibleInfillStrategy.NONE, cstr_infill: builtins.bool = False, cstr_strategy: ConstraintStrategy = ConstraintStrategy.MC, qei_config: QEiConfig = ..., infill_optimizer: InfillOptimizer = InfillOptimizer.COBYLA, trego: typing.Optional[typing.Any] = None, coego_n_coop: builtins.int = 0, target: builtins.float = -1.7976931348623157e+308, failsafe_strategy: FailsafeStrategy = FailsafeStrategy.REJECTION, seed: typing.Optional[builtins.int] = None, outdir: typing.Optional[builtins.str] = None, warm_start: builtins.bool = False, hot_start: typing.Optional[typing.Any] = None, verbose: typing.Optional[typing.Any] = None) -> Egor: ...
     def minimize(self, fun: typing.Any, fcstrs: typing.Sequence[typing.Any] = [], fcstr_specs: typing.Sequence[CstrSpec] = [], max_iters: builtins.int = 20, run_info: typing.Optional[typing.Any] = None, outdir: typing.Optional[builtins.str] = None, warm_start: builtins.bool = False, hot_start: typing.Optional[typing.Any] = None, seed: typing.Optional[builtins.int] = None, timeout: typing.Optional[builtins.float] = None, verbose: typing.Optional[typing.Any] = None) -> EgorOptim:
         r"""
         This function finds the minimum of a given function "fun"
@@ -282,14 +280,12 @@ class Egor:
                 Start by loading initial doe from <outdir> directory
 
             hot_start (bool, int >= 0 or None):
-                When True, hot_start behaves like hot_start=0 with no iteration extension.
                 When hot_start>=0 saves optimizer state at each iteration and starts from a previous checkpoint
-                if any for the given hot_start number of iterations beyond the max_iters nb of iterations.
+                for the given hot_start number of iterations beyond the max_iters nb of iterations.
                 In an unstable environment were there can be crashes it allows to restart the optimization
                 from the last iteration till stopping criterion is reached. Just use hot_start=0 in this case.
-                When specifying an extended nb of iterations (hot_start > 0) it can allow to continue till max_iters +
-                hot_start nb of iters is reached (provided the stopping criterion is max_iters)
-                Checkpoint information is stored in .checkpoint/egor.arg binary file.
+                When True, hot_start behaves like hot_start=0 with no iteration extension.
+                Checkpoint information is stored in .checkpoint or under outdir if outdir is specified.
 
             seed (int >= 0):
                 Random generator seed to allow computation reproducibility.
@@ -1246,24 +1242,6 @@ class ExitStatus(enum.Enum):
     Solver unexpected exit. See logs for details.
     """
 
-@typing.final
-class FeasibleInfillStrategy(enum.Enum):
-    r"""
-    Expected Feasible Improvement (EFI) strategy for hidden constraints.
-    """
-    NONE = ...
-    r"""
-    Do not use feasibility information.
-    """
-    EFI_P = ...
-    r"""
-    Expected feasible improvement weighted by full viability probability.
-    """
-    EFI_FE = ...
-    r"""
-    Feasibility-enhanced expected feasible improvement (more exploratory).
-    """
-
 @typing.final
 class FailsafeStrategy(enum.Enum):
     r"""
@@ -1285,6 +1263,25 @@ class FailsafeStrategy(enum.Enum):
     to learn which regions of the search space are more likely to fail and avoid them in the future
     """
 
+@typing.final
+class FeasibleInfillStrategy(enum.Enum):
+    r"""
+    Expected Feasible Improvement (EFI) is an acquisition function that takes into account the feasibility of the points in the optimization process.
+    It is defined as the product of the Expected Improvement (EI) weighted by the probability of viability
+    """
+    NONE = ...
+    r"""
+    Do not use feasibility information
+    """
+    EFI_P = ...
+    r"""
+    Use Expected Feasible Improvement with full probability of feasibility
+    """
+    EFI_FE = ...
+    r"""
+    Use Expected Feasible Improvement with 0.3 weighted probability of feasibility, which is more exploratory than EfiP
+    """
+
 @typing.final
 class InfillOptimizer(enum.Enum):
     r"""

diff --git a/python/egobox/examples/website_egor.py b/python/egobox/examples/website_egor.py
@@ -0,0 +1,22 @@
+import numpy as np
+
+import egobox as egx
+
+
+def objective(x: np.ndarray) -> np.ndarray:
+    x = np.atleast_2d(x)
+    return (x - 3.5) * np.sin((x - 3.5) / np.pi)
+
+
+def optimize_example() -> egx.EgorOptim:
+    return egx.Egor([[0.0, 25.0]]).minimize(objective, max_iters=20, seed=42)
+
+
+def main() -> None:
+    optim = optimize_example()
+    print(f"Optimization f={optim.result.y_opt} at {optim.result.x_opt}")
+    print(f"Status {optim.status.exit} in {optim.status.elapsed_time}s")
+
+
+if __name__ == "__main__":
+    main()